One of the main aims of the NIH Data Commons Pilot Phase Consortium (DCPPC) is to develop and apply guidelines that will allow biomedical digital object products and services to increasingly comply with the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles. To date, the FAIR principles have been published [1] and elaborated [2], but many aspects of how these principles should be specifically implemented for particular digital objects remain underspecified. We propose to pilot several efforts to bring FAIR to practice for a variety of biological and biomedical digital resources. We will produce prototype software solutions and employ crowdsourcing methods to engage a variety of stakeholders throughout the project life cycle. Community engagement and outreach are essential to evaluate and improve FAIR metrics, and to ensure that these metrics are useful for researchers, as well as funders, publishers, curators, developers, and other stakeholders. In accordance, we will establish a GO FAIR [3] node to facilitate governance and policies for the FAIRness component of the NIH Data Commons. Our work will include community input to specify how each FAIR principle should be interpreted in different specific contexts, thus ensuring that subject-matter experts can provide insight into what FAIR means within their discipline. Once FAIR metrics have been established, digital objects in each domain can be evaluated. To achieve this, we will employ crowdsourcing methods to capture and report FAIRness for a variety of digital objects starting with those relevant to TOPMed, GTEx, and MOD databases, including datasets, software tools, and publications. We will develop a prototype software platform called FAIRShake to enable producers of digital objects, as well as the scientific community that participates in the crowdsourcing project, to assess digital objects by entering information into a form according to the FAIR criteria that will be developed in the first phase of this project. We will design FAIRshake as an element of the broader ecosystem of FAIR services, specifically linking it to the FAIRsharing resource and to those from the nascent GO FAIR initiative. The collected FAIRness assessment data will be stored in a database, and will be used to calculate statistics and perform other forms of high-level assessment to gauge the FAIR compliance of digital objects. The overall assessment will be visualized as a FAIRness status insignia that will be inserted into web pages enlisting the digital objects. We foresee that this new software platform will work with existing resources through API and a browser extension. Datasets, tools, and publications associated with GTEx, TOPMed, and MOD will be assessed for FAIRness, and recommendations will be provided for remediation of any gaps in FAIRness that may be identified. By developing consistent FAIR guidelines and metrics, creating the FAIRshake ecosystem to manage FAIRness assessments, evaluating the FAIRness of the three designated example digital resources, and establishing the FAIR governing body, we will significantly advance efforts to enhance and standardize the FAIRness of biomedical digital resources while ensuring that members of the research community are active participants in contributing to these developments.